Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "225"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 225 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 225, Node N19:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 RF_ok 100.00% 0.00% 90.60% 0.00% - - -0.549569 14.831721 0.467599 5.667915 -0.828529 6.710999 -1.618346 1.501647 0.5762 0.1422 0.4619 nan nan
2460014 RF_ok 100.00% 0.00% 100.00% 0.00% - - -1.245402 12.576900 0.153534 3.865595 -0.680423 10.134255 -1.316188 1.070861 0.5492 0.1008 0.4612 nan nan
2460013 RF_ok 100.00% 0.00% 90.92% 0.00% - - -0.573215 14.862056 0.525578 5.612661 -0.786568 6.752264 -1.507852 2.436183 0.5697 0.1345 0.4668 nan nan
2460012 RF_ok 100.00% 0.00% 89.79% 0.00% - - -0.595805 13.934788 0.417917 5.442044 -0.920160 7.430887 -2.169220 2.837564 0.5735 0.1404 0.4626 nan nan
2460011 RF_ok 100.00% 0.00% 87.53% 0.00% - - -0.161415 14.975919 0.847489 7.221505 -0.884636 15.408933 -1.359581 2.297698 0.5828 0.1445 0.4785 nan nan
2460010 RF_ok 100.00% 0.00% 86.87% 0.00% - - -0.163450 16.293191 1.091891 6.078314 -0.470613 10.056215 -1.338605 2.102635 0.5955 0.1491 0.4861 nan nan
2460009 RF_ok 100.00% 0.00% 86.27% 0.00% - - -0.171267 15.020706 0.935818 6.858720 -0.545814 8.479043 -1.767700 2.257084 0.5983 0.1546 0.4869 nan nan
2460008 RF_ok 100.00% 0.00% 60.00% 0.00% - - -0.243510 18.489187 1.030575 7.390569 -0.477237 7.496037 -0.142141 4.898718 0.6324 0.1991 0.4911 nan nan
2460007 RF_ok 100.00% 0.00% 82.13% 0.00% - - -0.490464 13.918360 0.556905 5.808059 -0.772222 6.955020 -1.279221 2.365040 0.6019 0.1552 0.4842 nan nan
2459999 RF_ok 0.00% 0.00% 99.42% 0.00% - - nan nan nan nan nan nan nan nan 0.6181 0.1033 0.2795 nan nan
2459998 RF_ok 100.00% 0.00% 90.32% 0.00% - - -0.435133 11.708280 0.542114 4.774911 -0.571828 9.878399 -1.323641 1.780768 0.5997 0.1358 0.4951 nan nan
2459997 RF_ok 100.00% 0.00% 89.89% 0.00% - - -0.272139 12.763311 0.851472 5.217960 -0.641417 9.285670 -1.824207 2.754427 0.6108 0.1435 0.4940 nan nan
2459996 RF_ok 100.00% 0.00% 87.41% 0.00% - - 0.057299 13.692040 0.866734 6.592055 -0.762275 8.900217 -1.320179 1.160762 0.6218 0.1511 0.5069 nan nan
2459995 RF_ok 100.00% 0.00% 83.24% 0.00% - - -0.109490 13.999973 0.844381 5.886205 -0.572624 9.159324 -1.395213 0.970558 0.6159 0.1522 0.4976 nan nan
2459994 RF_ok 100.00% 0.00% 89.90% 0.00% - - -0.505806 13.667947 0.714949 5.123507 -0.852212 9.265966 -1.216207 0.762569 0.6108 0.1404 0.4993 nan nan
2459993 RF_ok 100.00% 0.00% 97.39% 0.00% - - -0.386305 12.838396 0.943763 4.462579 -0.684553 10.660074 -1.064981 2.380908 0.5971 0.1095 0.5016 nan nan
2459991 RF_ok 100.00% 0.00% 94.81% 0.00% - - -0.532760 15.989284 0.837437 4.863295 -0.718906 10.462438 -1.054365 0.911865 0.6028 0.1199 0.5129 nan nan
2459990 RF_ok 100.00% 0.00% 91.74% 0.00% - - -0.497594 13.181641 0.785641 4.614999 -0.680391 10.766344 -1.290638 0.614324 0.6067 0.1268 0.4993 nan nan
2459989 RF_ok 100.00% 0.00% 91.95% 0.00% - - -0.622871 13.318005 0.901973 4.337721 -0.767606 9.017480 -1.196924 0.329169 0.6075 0.1291 0.5021 nan nan
2459988 RF_ok 100.00% 0.00% 91.95% 0.00% - - -0.672815 15.617793 0.799478 4.681188 -0.887185 12.895525 -1.172455 0.499788 0.6088 0.1334 0.5010 nan nan
2459987 RF_ok 100.00% 0.00% 89.52% 0.00% - - -0.562505 13.053163 0.738944 4.852280 -0.790846 7.754582 -1.342791 1.820509 0.6110 0.1417 0.4928 nan nan
2459986 RF_ok 100.00% 0.00% 67.87% 0.00% - - -0.411426 15.975549 0.824322 5.155710 -0.845666 10.956474 -0.767693 9.022449 0.6369 0.1888 0.4954 nan nan
2459985 RF_ok 100.00% 0.00% 89.08% 0.00% - - -0.461000 14.390586 0.680884 4.875191 -0.995882 8.345335 -1.637674 1.865166 0.6171 0.1412 0.5056 nan nan
2459984 RF_ok 100.00% 0.00% 81.67% 0.00% - - -0.368139 13.784398 0.827147 5.159750 -0.198687 11.781676 -0.084885 3.775051 0.6314 0.1713 0.4963 nan nan
2459983 RF_ok 100.00% 0.00% 73.04% 0.00% - - -0.669788 13.628506 0.728838 4.631454 -1.114246 10.863366 -0.999414 5.711964 0.6328 0.1853 0.4943 nan nan
2459982 RF_ok 100.00% 0.00% 57.86% 0.00% - - -1.179010 11.406553 0.116680 4.106878 -0.982090 5.147744 -1.052124 2.741084 0.6965 0.2349 0.5184 nan nan
2459981 RF_ok 100.00% 0.00% 91.73% 0.00% - - -0.696491 12.610679 0.885659 4.739767 -0.864181 12.057906 -1.473871 0.831085 0.6163 0.1359 0.5065 nan nan
2459980 RF_ok 100.00% 0.00% 68.40% 0.00% - - -0.981217 12.062659 0.506421 4.440364 -1.209325 10.547372 -0.458912 4.589632 0.6605 0.2060 0.4978 nan nan
2459979 RF_ok 100.00% 0.00% 93.51% 0.00% - - -0.871378 12.702381 0.536967 4.026978 -0.703798 9.843934 -1.288309 0.587711 0.6085 0.1281 0.5090 nan nan
2459978 RF_ok 100.00% 0.00% 93.41% 0.00% - - -0.819833 12.887848 0.732450 4.331719 -0.655372 10.697958 -1.197168 1.168815 0.6098 0.1272 0.5117 nan nan
2459977 RF_ok 100.00% 0.00% 97.32% 0.00% - - -0.469378 13.566399 0.561880 4.505508 -0.635719 10.956538 -1.339956 1.209230 0.5729 0.1287 0.4638 nan nan
2459976 RF_ok 100.00% 0.00% 91.30% 0.00% - - -0.650795 13.103691 0.621683 4.511652 -0.658617 10.589717 -1.013523 1.386269 0.6189 0.1345 0.5147 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 225: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 14.831721 14.831721 -0.549569 5.667915 0.467599 6.710999 -0.828529 1.501647 -1.618346

Antenna 225: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.576900 -1.245402 12.576900 0.153534 3.865595 -0.680423 10.134255 -1.316188 1.070861

Antenna 225: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 14.862056 -0.573215 14.862056 0.525578 5.612661 -0.786568 6.752264 -1.507852 2.436183

Antenna 225: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.934788 -0.595805 13.934788 0.417917 5.442044 -0.920160 7.430887 -2.169220 2.837564

Antenna 225: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Temporal Variability 15.408933 -0.161415 14.975919 0.847489 7.221505 -0.884636 15.408933 -1.359581 2.297698

Antenna 225: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 16.293191 -0.163450 16.293191 1.091891 6.078314 -0.470613 10.056215 -1.338605 2.102635

Antenna 225: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 15.020706 -0.171267 15.020706 0.935818 6.858720 -0.545814 8.479043 -1.767700 2.257084

Antenna 225: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 18.489187 18.489187 -0.243510 7.390569 1.030575 7.496037 -0.477237 4.898718 -0.142141

Antenna 225: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.918360 -0.490464 13.918360 0.556905 5.808059 -0.772222 6.955020 -1.279221 2.365040

Antenna 225: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 225: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 11.708280 -0.435133 11.708280 0.542114 4.774911 -0.571828 9.878399 -1.323641 1.780768

Antenna 225: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.763311 -0.272139 12.763311 0.851472 5.217960 -0.641417 9.285670 -1.824207 2.754427

Antenna 225: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.692040 0.057299 13.692040 0.866734 6.592055 -0.762275 8.900217 -1.320179 1.160762

Antenna 225: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.999973 -0.109490 13.999973 0.844381 5.886205 -0.572624 9.159324 -1.395213 0.970558

Antenna 225: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.667947 -0.505806 13.667947 0.714949 5.123507 -0.852212 9.265966 -1.216207 0.762569

Antenna 225: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.838396 -0.386305 12.838396 0.943763 4.462579 -0.684553 10.660074 -1.064981 2.380908

Antenna 225: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 15.989284 -0.532760 15.989284 0.837437 4.863295 -0.718906 10.462438 -1.054365 0.911865

Antenna 225: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.181641 13.181641 -0.497594 4.614999 0.785641 10.766344 -0.680391 0.614324 -1.290638

Antenna 225: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.318005 13.318005 -0.622871 4.337721 0.901973 9.017480 -0.767606 0.329169 -1.196924

Antenna 225: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 15.617793 15.617793 -0.672815 4.681188 0.799478 12.895525 -0.887185 0.499788 -1.172455

Antenna 225: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.053163 -0.562505 13.053163 0.738944 4.852280 -0.790846 7.754582 -1.342791 1.820509

Antenna 225: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 15.975549 15.975549 -0.411426 5.155710 0.824322 10.956474 -0.845666 9.022449 -0.767693

Antenna 225: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 14.390586 14.390586 -0.461000 4.875191 0.680884 8.345335 -0.995882 1.865166 -1.637674

Antenna 225: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.784398 -0.368139 13.784398 0.827147 5.159750 -0.198687 11.781676 -0.084885 3.775051

Antenna 225: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.628506 -0.669788 13.628506 0.728838 4.631454 -1.114246 10.863366 -0.999414 5.711964

Antenna 225: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 11.406553 -1.179010 11.406553 0.116680 4.106878 -0.982090 5.147744 -1.052124 2.741084

Antenna 225: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.610679 12.610679 -0.696491 4.739767 0.885659 12.057906 -0.864181 0.831085 -1.473871

Antenna 225: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.062659 12.062659 -0.981217 4.440364 0.506421 10.547372 -1.209325 4.589632 -0.458912

Antenna 225: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.702381 -0.871378 12.702381 0.536967 4.026978 -0.703798 9.843934 -1.288309 0.587711

Antenna 225: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 12.887848 12.887848 -0.819833 4.331719 0.732450 10.697958 -0.655372 1.168815 -1.197168

Antenna 225: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.566399 -0.469378 13.566399 0.561880 4.505508 -0.635719 10.956538 -1.339956 1.209230

Antenna 225: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
225 N19 RF_ok nn Shape 13.103691 13.103691 -0.650795 4.511652 0.621683 10.589717 -0.658617 1.386269 -1.013523
In [ ]: